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Titlebook: Runtime Verification; 20th International C Jyotirmoy Deshmukh,Dejan Ni?kovi? Conference proceedings 2020 Springer Nature Switzerland AG 202

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樓主: PED
21#
發(fā)表于 2025-3-25 05:52:51 | 只看該作者
Placement of Runtime Checks to Counteract Fault Injectionsthe data or not. We show that checks in loops induce simple and natural loop invariants that we can use to speed up the verification process..The abstractions let us trade verification time against the number of required runtime checks, allowing us to find efficient sets of integrity checks for crit
22#
發(fā)表于 2025-3-25 09:36:40 | 只看該作者
23#
發(fā)表于 2025-3-25 14:55:01 | 只看該作者
Runtime Verification of Autonomous Driving Systems in CARLAe recently introduced . library, for runtime verification of STL (Signal Temporal Logic) specifications, with the CARLA simulator. Finally, we also present the obtained results from monitoring quantitatively interesting requirements for an experimental Adaptive Cruise Control system tested in CARLA.
24#
發(fā)表于 2025-3-25 15:56:14 | 只看該作者
25#
發(fā)表于 2025-3-25 20:40:04 | 只看該作者
26#
發(fā)表于 2025-3-26 01:57:36 | 只看該作者
Assurance of Distributed Algorithms and Systems: Runtime Checking of Safety and Livenesslanguages, but precisely specified and directly executable, as in formal specification languages and practical programming languages, respectively. The checking framework, as well as the writing of distributed algorithms and specification of their safety and liveness properties, use DistAlgo, a high
27#
發(fā)表于 2025-3-26 08:04:27 | 只看該作者
Analysing the Performance of Python-Based Web Services with the , Frameworking our theoretical contributions which take the form of an engineer-friendly specification language; instrumentation and monitoring algorithms; and an approach for explanation of property violations. We then summarise the . ecosystem, which includes an intuitive library for writing specifications a
28#
發(fā)表于 2025-3-26 10:55:22 | 只看該作者
29#
發(fā)表于 2025-3-26 15:53:22 | 只看該作者
30#
發(fā)表于 2025-3-26 19:36:59 | 只看該作者
Runtime-Safety-Guided Policy Repairmance learning-based control policy (e.g. one trained as a neural network) is paired with a model-based safety controller. The safety controller is endowed with the abilities to predict whether the trained policy will lead the system to an unsafe state, and take over control when necessary. While th
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